Multi-FusNet of Cross Channel Network for Image Super-Resolution Article Swipe
Watchara Ruangsang
,
Supavadee Aramvith
,
Takao Onoye
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/access.2023.3282571
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/access.2023.3282571
Image Super-resolution (SR) has gained considerable attention in artificial intelligence (AI) research and image-based applications. Recent deep learning-based SR models have demonstrated remarkable accuracy and perceptual quality in the resulting images. However, the computational cost and model parameters are the most challenging limitations in real-world applications. Additionally, designing an efficient and lightweight SR algorithm to improve the perceptual quality of the SR images is a critical issue. According to these considerations, we propose a Multi-FusNet of Cross Channel Network (MFCC) network by modeling a multipath residual network, named multi-RG, with cross-filtering fusion. Additionally, a pixel shuffling fusion technique is used to fuse low-level features into the up-sampled features of the multi-RG. The experimental results show the comparison of the proposed MFCC to the state-of-the-art SR models. The proposed method significantly reduces the number of network parameters (8.4 times compared to RCAN) while preserving the visual quality of the result and achieving the best PSNR value compared to the other state-of-the-art methods.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2023.3282571
- https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143181.pdf
- OA Status
- gold
- Cited By
- 8
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4379184258
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4379184258Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2023.3282571Digital Object Identifier
- Title
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Multi-FusNet of Cross Channel Network for Image Super-ResolutionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-01Full publication date if available
- Authors
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Watchara Ruangsang, Supavadee Aramvith, Takao OnoyeList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2023.3282571Publisher landing page
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https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143181.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/10005208/10143181.pdfDirect OA link when available
- Concepts
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Computer science, Artificial intelligence, Fuse (electrical), Residual, Image fusion, Pixel, Channel (broadcasting), Image (mathematics), Artificial neural network, Pattern recognition (psychology), Computer vision, Algorithm, Electrical engineering, Computer network, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
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59Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3013529009, https://openalex.org/W2967788068, https://openalex.org/W1885185971, https://openalex.org/W54257720, https://openalex.org/W6730637201, https://openalex.org/W2779812541, https://openalex.org/W1485966307, https://openalex.org/W2194775991, https://openalex.org/W2242218935, https://openalex.org/W2895598217, https://openalex.org/W2963645458, https://openalex.org/W1930824406, https://openalex.org/W6638194035, https://openalex.org/W6729059855, https://openalex.org/W2954930822, https://openalex.org/W2476548250, https://openalex.org/W2967403871, https://openalex.org/W4206211125, https://openalex.org/W4210600945, https://openalex.org/W3202310860, https://openalex.org/W3207299541, https://openalex.org/W2741137940, https://openalex.org/W2577659785, https://openalex.org/W2547247145, https://openalex.org/W3000009229, https://openalex.org/W2919600643, https://openalex.org/W3127723530, https://openalex.org/W3011179489, https://openalex.org/W2921765345, https://openalex.org/W6697462184, https://openalex.org/W2963372104, https://openalex.org/W2866634454, https://openalex.org/W2503339013, https://openalex.org/W3040726448, https://openalex.org/W2795024892, https://openalex.org/W2963729050, https://openalex.org/W2740139074, https://openalex.org/W2976718572, https://openalex.org/W2917797023, https://openalex.org/W6735992568, https://openalex.org/W4226052488, https://openalex.org/W2964277374, https://openalex.org/W6761511153, https://openalex.org/W3163767593, https://openalex.org/W2747898905, https://openalex.org/W2214802144, https://openalex.org/W2963610452, https://openalex.org/W3129158555, https://openalex.org/W6784619216, https://openalex.org/W2607041014, https://openalex.org/W2964125708, https://openalex.org/W2964101377, https://openalex.org/W2962685937, https://openalex.org/W2541674938, https://openalex.org/W2560215812, https://openalex.org/W2603322229, https://openalex.org/W3112326203, https://openalex.org/W1791560514, https://openalex.org/W2935564801 |
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| abstract_inverted_index.SR | 18, 52, 61, 124 |
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| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
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| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
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| citation_normalized_percentile.is_in_top_10_percent | False |